1. Field of the Invention
This invention relates to techniques for managing data and particularly to an event correlation engine for managing different rules which process events for correlation purposes.
2. Description of the Related Art
A typical correlation engine has hundreds or thousands of different rules that must be applied for evaluation of incoming events. Normally, only some of the rules are computed or evaluated for each event. Processing all of the rules would dramatically reduce the efficiency of the correlation engine and cause low performance. Presently, one way for avoiding such performance issues is to categorize incoming events by using an “event type” attribute. This technique, and similar techniques, call for classifying each rule by the event type accepted by the respective rule. These classification techniques provide one way to improve processing performance. Unfortunately, these techniques also expose classification of the events to the rules definition language, thereby decreasing efficiency. With the growing complexity of information systems and the growing need for analysis power, techniques for classification relying on a single attribute will soon be outmoded. The soon to be realized obsolescence thus calls for classification involving multiple attributes.
What is needed is a low overhead technique for improving the performance of event correlation engines. Preferably, the technique is not based on event type classification alone and does not require any changes to rule representation languages. The technique should also support multi-dimensional classification, thus providing for improved accuracy regarding possible rules (a subset of target rules to be evaluated) for each event processed in the correlation engine. When the correlation engine implements the technique, the correlation engine should support a much larger set of rules with better performance results than is possible with current technologies.
One example of a prior art technique is disclosed in U.S. Pat. No. 6,563,952 B1, entitled “Method and Apparatus for Classification of High Dimensional Data’, issued May 13, 2003, to Srivastava et al. This patent discloses, an apparatus and method for classifying high-dimensional sparse datasets.